Honors Program Theses


Open Access Honors Program Thesis

First Advisor

Ben Schafer


There are many sources for stock market information and an investor can tap into the television or online media to sync up with current market news. Popular sources are news channels such as CNBC or CNN who spend the better part of the day evaluating the stock market. The internet is filled with a wealth of data ranging from historical to current market information. Added to this information are countless websites that make predictions on what stocks should be bought or sold. The challenge with all of this information is to figure out which sources are actually valid and can be used to make decisions on personal stock portfolios. Websites such as www.etrade.com and www.moneycontrol.com give investors a lot of advice on the stocks to buy and sell, however they do not provide many tools for an investor to conduct their own research. Within all of these constraints lies the need for a new analysis tool and the subject of this project.

Fundamental Stock Market Analysis is primarily statistical in nature. Financial ratios and numbers that an analyst would look for are calculated from the annual and quarterly financial reports that companies release. It seems reasonable to have a computer program to make these calculations for the analyst and present information in a format where the analyst can spend more time analyzing the calculated information.

Year of Submission



Department of Computer Science

University Honors Designation

A thesis submitted in partial fulfillment of the requirements for the designation University Honors


If you are the rightful copyright holder of this thesis and wish to have it removed from the Open Access Collection, please submit a request to scholarworks@uni.edu and include clear identification of the work, preferably with URL.

Date Original


Object Description

1 PDF file (27 pages)